Organs-specific metabolomics and anticholinesterase activity suggests a trade-off between metabolites for therapeutic advantages of Trillium govanianum Wall. ex D. Don

Trillium govanianum is traditionally used to treat innumerable alignments like sexual disorders, cancer, inflammation etc. Mainly rhizomes of T. govanianum have been explored for phytochemical profiling but comprehensive metabolomics of other parts has not been yet deeply investigated. Thus, current study was aimed for organs-specific (roots, rhizomes, rhizomatous buds, stems, leaves, and fruits) phytochemical profiling of T. govanianum via metabolomics approach. Targeted (steroidal saponins and free sugars) and non-targeted metabolomics were performed by UPLC-PDA/ELSD & UHPLC-Q-TOF-IMS. Among steroidal compounds, 20-hydroxyecdysone, pennogenin-3-O-β-chacotrioside, dioscin were found predominantly in all samples while diosgenin was identified only in rhizomes. Further, four free sugars viz. 2-deoxyribose (116.24 ± 1.26 mg/g: leaves), fructose (454.76 ± 12.14 mg/g: rhizomes), glucose (243.21 ± 7.53 mg/g: fruits), and galactose (69.06 ± 2.14 mg/g: fruits) were found significant in respective parts of T. govanianum. Elemental analysis of targeted samples was determined by atomic absorption spectrophotometer. Heavy metals (Cd, Hg, Pd, As) were absent while micro- (Mn, Na, Zn, Cu) and macro- (Ca, Fe, Mg, K) elements were found in all samples. Furthermore, UHPLC-Q-TOF-IMS had identified 103 metabolites based on their mass fragmentation patterns and 839 were tentatively predicted using METLIN database. The multivariate statistical analysis showed organs specific clustering and variance of metabolites. Apart from this, extracts were evaluated for in vitro anticholinesterase activity, and found potentials inhibitors with IC50 values 2.02 ± 0.15 to 27.65 ± 0.89 mg/mL and 3.58 ± 0.12 to 16.81 ± 2.48 mg/mL of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzyme, respectively. Thus, comprehensive metabolomics and anti-cholinesterase activity of different parts of T. govanianum would lay the foundation for improving medicinal importance and health benefits of T. govanianum.


UPLC-PDA
Ultra performance liquid chromatography photo diode array ESI-MS Electro spray ionisation mass spectrometry UHPLC-QTOF-IMS Ultra high-performance liquid chromatography -quadrupole time of flight mass spectrometry UHPLC Ultra-high performance liquid chromatography PCA Principal component analysis HCA Hierarchical cluster analysis AOAC Association of analytical communities HMBD Human Metabolome Database AD Alzheimer's disease Trillium govanianum Wall.ex D. Don, a herb belonging to family Melanthiaceae has been used traditionally for the treatment of cancer, sepsis, neurasthenia, dysentery, backache, wounds, inflammation, skin boils, reproductive disorder, menstrual and sexual disorders 1,2 .It is commonly known as "Nag Chhatri" and distributed in the Himalaya from Nanga Parbat (Gilgit-Baltistan) to Namcha Barwa (Tibet) at an altitude of 2400-3500 m amsl 3 .Pharmacologically, this species was reported to have anticancer, antifungal, antioxidant, antidiabetic, and antiinflammatory activities [4][5][6] .These medicinal properties might be attributed due to the presence of bioactive compounds like saponins, glycosides, terpenoids, phenolics, and flavonoids 7,8 .The phytochemical investigation of rhizomatous parts revealed to contain a high-value saponins of steroidal type like govanoside A, 20-hydroxyecdysone, pennogenin, and 5,20-dihydroxyecdysone 7,9,10 .Earlier reports also suggested the presence of diosgenin in T. govanianum rhizomes which is an important corticosteroid hormone that is utilized to form sex hormones and various steroidal drugs 11,12 .Although, in addition to rhizomes, aerial parts of T. govanianum also hold valuable importance.Earlier report on aerial parts (stems, leaves, fruits) had shown the presence of polyphenols as well as their free radicals scavenging and antidiabetic potential 5 .But, the comprehensive profiling of metabolites in the aerial parts are entirely unexplored.Thus, employment of analytical techniques is necessary to understand the metabolic flux in the aerial parts of T. govanianum.Recently, metabolomics approach has been become as one of the most widely used and meaningful analytical technique for the comprehensive profiling of metabolites in plants 13 .Metabolomics study was accomplished by two strategies, i.e. untargeted and targeted compounds identification and quantification, which have been adopted by researchers 14 .However, untargeted approach gathers a huge coverage on metabolites from dataset account.The plant metabolomics is a most rational approach and performed by advanced analytical tool in combination with multivariate statistical analysis (MSA) to monitor quality, variability, and similarities among the different samples 15,16 .To date, various tools have been applied for metabolomics studies but mass spectrometry (MS)-coupled techniques provide a very high sensitivity and detection ability to less abundant metabolites.UHPLC-DAD-Q-TOF-MS 2 is another choice of important tool for phytochemicals profiling in plant extracts [17][18][19] .Previously, metabolomics study was performed for ethanol and water extract of T. govanianum rhizomes only that described the identification of 26 metabolites 3 .Hence, in the current investigation, an UHPLC-QTOF-IMS was used for comprehensive metabolites profiling in aerial (stem, leaves, and fruits) and underground organs (roots, rhizomes, and rhizomatous buds) of T. govanianum.Both untargeted and targeted metabolomics studies were applied to understand specialized metabolites and their metabolic fluidity in different organs extracts.The widely known statistical inference were further used to analyse the variability in terms of similarities and differences among different samples.Multivariate statistical analysis including heatmaps, ven-diagram, stacked charts, principal component/coordinate analysis (PCA and PCoA) and hierarchical clustering analysis (HCA) were employed to screen out constituents that could help as part-specific markers of T. govanianum.Apart from this, acetylcholinesterase/butyrylcholinesterase inhibitory potential of different organs of T. govanianum was also investigated.To the best of our knowledge, this will be the first metabolomics assessment study that provide the metabolome information of whole plant.This report will shed light on the chemo-information, especially for ignored aerial parts (stem, leaves, and fruits).This is an important to understand its therapeutics and nutraceutical importance of underutilized parts.

Results
In current metabolomics studies, fresh materials of different organs (stems, leaves, fruits, rhizomatous bud, roots, rhizomes) of T. govanianum were extracted with ethanol and extracts were subjected for metabolomics study (Fig. S1).For targeted analysis of steroidal compounds (compounds 1-5), an UPLC-PDA-based method was developed and validated as per ICH guidelines.The calibration curves of all five compounds (1-5) were found linear in concentration range of 3.906-500 µg/mL and coefficient of regression (r 2 ) was in range of 0.994-0.998(Fig. S2).Limit of detection (LOD) and limit of quantification (LOQ) of compounds 1-5 were found in the range 3.35-7.26and 10.15-22.00,µg/mL respectively.The relative standard deviation (RSD) values were observed 0.44-1.23%and 0.75-2.08% for intraday (n = 3) and interday (n = 3) precisions, respectively (Table S1).Further, the recoveries study of each analyte was performed in ethanolic extract of rhizomes and found in the assortment of ˃80% (Table S1).The rt and area of the peak was found constant on repetitive conditions.These findings suggested that method is sensitive, stable, and accurate for the concurrent qualitative and quantitative analysis of compounds 1-5 in different parts of T. govanianum.

Quantification of steroidal compounds (compounds 1-5) in different parts
T. govanianum is known to contain steroidal saponins in rhizomes which plays an important role in biological activities.The validated UPLC-PDA method was employed for the qualitative and quantitative estimation of 4 steroidal (pennogenin-3-O-β-chacotrioside, dioscin, trillin, diosgenin) and one ecdysteroid

Free sugars quantification in different parts
Carbohydrates play a crucial role in biochemical and physiological processes, and overall plant functioning, including imparting adaptation abilities.Various sugars have been reported to protect from cold and drought stresses, phosphorus deficiency, and pathogen attack 22 .UPLC-ELSD-based analysis showed clear chromatographic separation of nine sugars (2-deoxy-rhamnose, arabinose, fructose, galactose, glucose, mannose, myoinositol, rhamnose, and trehalose: Fig. S3).Four sugars were quantified among the nine targeted sugars in most of the T. govanianum organs.2-deoxyribose and fructose were quantified in all the extracts and highest in leaves (116.24 ± 1.26 mg/g) and rhizomes (454.76 ± 12.14 mg/g) extracts, respectively.Similarly, glucose (243.21 ± 7.53 mg/g) and galactose (69.06 ± 2.14 mg/g) were major in fruits as compared to other parts.Further, rhamnose, arabinose, mannose, myoinositol, and trehalose were not detected in any parts of T. govanianum (Table 1).

Elemental analysis in different parts
Trace elements of plant-based medicines are key components that helps in the treatment of metabolic disorders.Approximately, forty elements have been considered essential for the survival of animals and plants 23 .These elements act as coenzymes in metabolic processes 22 .Eight essential elements viz.Fe (Iron), Mn (Manganese), Ca (Calcium), Mg (Magnesium), Na (Sodium), K (Potassium), Zn (Zinc), and Cu (Copper) were found in the extracts of T. govanianum.Mg, K, and Fe were found highest in all samples as compared to other elements.Further, Fe was highest in roots (9.929 ± 0.072 mg/g) followed by fruits (3.935 ± 0.047 mg/g), leaves (3.480 ± 0.009 mg/g), rhizomatous buds (0.726 ± 0.013 mg/g), and rhizomes (0.033 ± 0.001 mg/g).Similarly, Mg (10.191 ± 0.065 mg/g) and K (12.052 ± 0.057 mg/g) were reported highest in rhizomatous buds and stems samples, respectively.Zn was found highest in stems (4.715 ± 0.015 mg/g) and rhizomes (1.629 ± 0.010) samples while Na was found in all samples except rhizomatous buds (Table 1).Further, Cu, Ca, Mn, and Ni was found in trace quantities, whereas Cr (Chromium) and toxic heavy elements viz.Pb (Lead), Cd (Cadmium) were found absent in the samples of T. govanianum.

Non-targeted metabolites profiling using UHPLC-QTOF-IMS
Metabolites of different parts of T. govanianum were profiled using UHPLC-QTOF-IMS.Total ion chromatograms (TIC) of different parts extract were analysed in positive ion mode and peaks were identified as individual metabolites (Fig. S4).The tentative identification of metabolites was assured with retention time, UV-VIS spectra, and mass spectra (precise mass, fragmentation pattern, and isotopic distribution).The exuded positive ion ESI mass spectra were found due to (M+H) + cations, out of which most of the spectra were due to the losses of sugar moieties.A schematic diagram was presented in Fig. 2 that showed steps of confident identification of pennogenin 24 .The extracted ion chromatograms (ESI-EIC) of its protonated adduct was detected with m/z 885.48 (M+H) + at retention time (RT) of 15.183 min.The predicted molecular formula for this adducts was C 45 H 72 O 17 .The sodiated (M+Na) + adduct was detected with m/z 907.46, with three intense and very prominent peaks by loss one rhamnose, two rhamnose, two rhamnose + one glucose were detected at m/z 739.42 (M+H-Rha) + , 593.36 (M+H-2Rha) + , 431.31 (M+H-2Rha-Glc) + respectively (Table 2 and Table S2) 24 .A total 103 molecules were identified based on their MS/MS spectral pattern in the samples of T. govanianum, which comprises of 6 carbohydrates, 11 terpenoids, 4 polyphenols, 5 flavonoids, 73 steroids and saponins, and 4 other organic compounds.The MS chromatogram, mass fragments, molecular formula briefly discussed in Table 2, S2 and Fig. S5.Further structures of identified compounds were depicted in Fig. 3A, B.

Metabolite profiling by METLIN data base
The acquired raw data from UHPLC-QTOF-IMS were searched against the METLIN database for the tentative identification of different classes of compounds.Accuracy score > 95% was selected for the identification of metabolites and total 839 compounds were identified through METLIN database in different samples such as roots (270), rhizomes (231), rhizomatous buds (233), stems (193), leaves (276), fruits (192) of T. govanianum (Table S3).Most of these compounds were commonly present in different organs of the plant.These identified metabolites were further classified in six different categories of compounds comprising of saponins (steroidal, www.nature.com/scientificreports/triterpenoid, and their derivatives; 289 metabolites), terpenoids (mono, bi, di, sesqui terpenoids; 140), glycosides (carbohydrates and derivatives; 110 metabolites), fatty acids (fatty esters, acid, saturated, and unsaturated fats; 48 metabolites), phenolics and flavonoids (138 metabolites) and other (organic, nitrogen-containing metabolites including amino acids and nucleobases; 114 metabolites).Doughnut diagrams showed the numbers of metabolites of different categories present in the six organs of the plant.The circles from inner to outsides represented the samples of roots, rhizomes, buds, stems, leaves and fruits, respectively.Among all the parts, roots and rhizomes were dominated with "steroids and saponins" (107 and 108).Similarly, leaves were found enriched with glycoside (54), phenolics and flavonoids (59) along with steroids and saponins (92) (Fig. 4A).Further, similarity and variation of metabolites among all the organs shown in venn diagram and social graph (Fig. 4A).Twelve metabolites were observed common in all the organs, whereas each organ contain unique metabolites viz.roots, rhizomes, rhizomatous buds, stems, leaves, and fruits were found enriched with 110, 80, 121, 61, 106, 56 metabolites, respectively (Fig. 4A).Social graph illustrated that the 80 metabolites of leaves were commonly present in different organs i.e., roots, rhizomes, rhizomatous buds, stems, and fruits contained 27, 9, 3, 19, and 22 common metabolites.Similarly, roots and rhizomes had 71 and 66 common metabolites with different organs parts of the plants (Fig. 4A).Furthermore, venn network plot indicated the relation of 839 identified metabolites with the different organs of T. govanianum (Fig. 4B).

Multivariate statistical analysis
Prior to the differential analysis, a principal component analysis (PCA) was conducted on data obtained from METALIN database to observe the degree of variation and similarity between different organs.PCA was used to identify data patterns and the analysis showed the data points were closely grouped or overlapped that demonstrated its good reproducibility.The first two principal components PC1 and PC2 explained 47.8% and 20.1% of the variability the dataset, respectively, and showed the association with different organs.In the PCA plot, rhizomatous buds were concentrated on the left lower quadrant (Q-III) of the plot, replicates of fruits, leaves, and rhizomes were distributed on the right lower quadrant (Q-IV), while stem and roots were distributed in the upper quadrants (Q-I & Q-II) (Fig. 5).Similarly, 3D scatter plot of PCA showed metabolites proliferation in three axes PC1, PC2, PC3 with percent variation accounted for PC-3 was 16% (Fig. 5).Further, a hierarchical cluster analysis (HCA) was plotted using the Z-score normalized metabolite content and showed the relationships of 839 metabolites with 6 different organs of T. govanianum.Metabolites with the same characteristics were identified using euclidean distance and were grouped according to complete linkage, following the intergroup variation of the metabolite characteristics were assessed.Heat map hierarchical clustering analysis showed the three main groups clustering along the horizontal direction.The first group included stems and leaves, the second group included roots and rhizomes and the third group included rhizomatous buds and fruits (Fig. 6A).This grouping illustrated in heat map represented the same characteristics of the metabolites along with intergroup variation of the metabolites were assessed along the vertical direction.The brown areas indicated the availability of specific compounds between samples.Identified metabolites (in METLIN database) were arranged based on their mass to charge ratio (m/z) and contributed significantly for the differentiation among the organs of T. govanianum.Metabolites were extracted by using VIP scores as a quantitative estimation of the discriminatory power of each individual metabolite.Overall, the top 15 metabolites with a VIP score greater than 5 were considered for the organ-specific informative metabolite markers (Fig. 6B).These metabolites suggest organ-specific alterations in polypodine B, steroid derivatives and fatty acids.VIP scores clearly showed the content of octadecanoic acid (m/z 351.215) and polypodine B (m/z 519.293) among the various organs of T. govanianum.It was observed that content of polypodine B was highest in roots followed by rhizomatous buds of T. govanianum (Fig. 6B).Further, HCA dendrogram clearly showed that the samples of rhizomatous buds were dramatically different as compared to other organs of T. govanianum (Fig. 6C).Thus, the PCA, HCA, VIP score plot and HCA dendrogram results suggested that metabolites differences may be responsible for the variation between samples grouping.

Quantified metabolites statistical analysis
The statistical analysis (heatmap, Ven-diagram, stacked charts, PCA, PCoA) were performed on targeted metabolites which showed similarities, discriminations, distributions, and variations among the different organs of T. govanianum.MVA using heat map and ballon plot clearly showed the differentiation among roots, rhizomes, rhizomatous buds, leaves, stems, and fruits samples of T. govanianum.The analysis provided useful information for the quantified metabolites and it was observed that greater the quantity of metabolites, greater will be the size of ballon/ heat colour.The results clearly showed that 20-hydroxyecdysone was present in all organs of T. govanianum while diosgenin was found only in rhizomes.Further, ballon plot showed that rhizomes were found enriched with dioscin and fructose, while fruits were rich in fructose, glucose, and galactose (Fig. S6).Further, correlation among various organs were shown by correlation diagram which provided the probability of similarities among various organs of the plant.It clearly showed that roots were closely associated with stems (P = 0.81) and leaves (P = 0.95), while rhizomes were in association with rhizomatous buds (P = 0.77) and fruits (P = 0.67).Among all samples, rhizomatous buds and stems were found closely associated with all the parts with P = 0.23-0.81.Normal probability plots also showed correlation coefficient in the range of 0.614-0.837(Fig. S6).

Cholinesterase inhibitory activity
Acetylcholinesterase (AChE) is found at postsynaptic neuromuscular junctions and immediately breaks down acetylcholine (natural neurotransmitter) into acetic acid and choline.These AChE helps to terminate neuronal transmission and signalling that causes problems in communication of neuronal signals and sometime causes Alzheimer's disease (AD).To prevent this neurotransmitter degradation through enzymes we had targeted to screen the samples for AChE and BChE enzymes inhibitory activity by in-vitro enzyme inhibition assays.The effect of T. govanianum samples were expressed as percentages of inhibition and IC 50 values were depicted in Table 3.The results of AChE inhibition by the extract revealed that among different samples, underground part extracts viz.rhizomes (IC 50 : 2.02 ± 0.15 mg/mL) exhibited highest inhibitory effect followed by roots (IC 50 : 5.69 ± 1.61 mg/mL) and rhizomatous buds (IC 50 : 8.42 ± 1.27 mg/mL) as compared to positive control i.e., galantamine (IC 50 : 3.6 ± 0.6 µg/mL) (Fig. 7).However, aerial parts i.e. stem, leaves, and fruits showed inhibition in the ranges of IC 50 : 11.30-27.65mg/mL.Similarly, underground parts such as roots (IC 50 : 3.58 ± 0.12 mg/mL) showed highest BChE inhibition followed by leaves (IC 50 : 4.72 ± 0.73 mg/mL) as compared to positive control galantamine (IC 50 : 32.0 ± 1.6 µg/mL; Table 3).

Discussion
The metabolomics study of the different parts of the T. govanianum were not conducted earlier and only the metabolomics of underground parts were reported 3 , because of the utilization and trade of underground parts in the market.Except few traditional uses in tribal communities the aerial parts were unutilized and waste for the traders and farmers.Therefore, to explore the potential of whole plants of T. govanianum, especially the aerial parts, the current study was designed to conduct a comprehensive metabolome analysis of different parts/ organs of aerial and underground parts.The comprehensive metabolome suggested that underground parts contain steroids, sugars and elements while aerial parts are rich in polyphenols, steroids, terpenoids and their derivatives.Earlier study also suggested that total phenolics, flavonoids as well as saponin were estimated in different aerial and underground parts.Polyphenolics were also profiled in both the samples 5 .In current study an accurate and simple UPLC-PDA method was developed, validated and used for the profiling of steroidal compounds (20-hydroxyecdysone, pennogenin-3-O-β-chacotrioside, dioscin, trillin, and diosgenin) in different parts samples of T. govanianum.The 20-hydroxyecdysone (phytoecdysteroids) was previously reported in water and ethanol extract of T. govanianum rhizomes 3 and our findings also revealed its presence in all samples.Further, dioscin is an important steroidal saponin and a well-known precursor for the synthesis of hormones as well as various synthetic contraceptives in pharmaceutical industries 12 .Dioscin and trillin can be converted into diosgenin (a cortico-steroid hormone) by hydrolysis process.Diosgenin is a precursor for the synthesis of progesterone (sex hormone) and also present in genus Trillium 11 .The dioscin content was found very high in rhizomes 33-34% and to best of our knowledge this is the first report for dioscin from T. govanianum.Further, the presence of sex hormones precursors in T. govanianum supports its traditional claim in the treatment of sexual disorders 11 .However, trillin was not detected in any sample of T. govanianum.This might be due to the low quantity of trillin in plant extracts or might be formed as a hydrolytic product of dioscin or related compounds.Similarly, free sugars analysis showed the presence of 2-deoxy-ribose, fructose, glucose, and galactose.Higher amount of fructose in rhizomes (454.76 ± 12.14 mg/g) and fruits (338.74 ± 5.94 mg/g) play an important role in the overall structural growth and enhance their tolerance to abiotic stresses like cold, drought and salinity 94 .Presence of sufficient amount of free sugars provide ability to plant for sustainability at high altitude environmental conditions 22 .Further, non-targeted metabolomics based on UHPLC-Q-TOF-IMS successfully profiled six organs/parts of T. govanianum.Total 103 metabolites were identified tentatively in T. govanianum samples and comprised of 6 carbohydrates, 11 terpenoids, 4 polyphenols, 5 flavonoids, 73 steroids and saponins, and 4 other organic compounds.Previously, UHPLC-Q-TOF-IMS-based metabolites profiling was able to report only 26 metabolites 3 and currently it was 103.This huge information on the metabolites will also be helpful to guide for isolation of metabolites as well as to set quality traits of the plant.Moreover, 839 metabolites of different classes were also identified and profiled using METLIN database search and that provided the beneficial information of metabolic flux among the different parts.The statistical analysis provided visual information about similarities and differences among the different samples in terms of organs.Furthermore, samples were screened for cholinesterase inhibitors through enzyme inhibition assays.As per the clinical evidences, cholinesterase inhibitors are one of the most capable treatments for neurodegenerative disorder especially, Alzheimer's disease 95 .Both AChE and BChE are the targets for inhibition because AChE predominates over BChE.As disease progresses, the activity of AChE declines in certain parts of brain to 10-15% of normal activity, whereas BChE activity increases to compensate the loss in AChE activity.Hence, inhibition of both enzymes is complimentary for treatment of mild-to-severe forms of AD.Plant derived molecules have also been shown cholinesterase inhibitory activity in addition to the approved drugs for AD.Therefore, underground parts (roots, rhizomes, and rhizomatous buds) showed better inhibition to both AChE and BChE enzymes as compared to the aerial parts (stems, leaves, and

Collection and identification of plant material
For collection of plants, all relevant permits/permissions have been obtained.In this study fresh plant materials of T. govanianum were collected from farmers' fields at Rajgundha of Barot valley, Distt-Kangra, in the month of August 2020.The experimental research and field studies on plants, including the collection of plant material comply with the institutional, national, and international guidelines and legislation.The specimen of plant was deposited at Biodiversity Division of CSIR-Institute of Himalayan Bioresource Technology, Palampur, H.P. India.The collected specimen was authenticated as "Trillium govanianum Wall.ex D. Don" (voucher specimen number: PLP-16470).Further, the aerial (stems, leaves, and fruits) and underground parts (roots, rhizomes, buds) of T. govanianum (5 g each) were separated and crushed to powder using mortar pestle.The crushed material of different parts was extracted with ethanol, using percolation for 24 h.Extracts were then filtered, dried under reduced pressure, and kept at 4 °C for further analysis.10 mg/mL concentration of each extract was prepared in HPLC grade methanol for further analysis of targeted and non-targeted metabolomics.Biological and technical samples were used in triplicates.

UPLC-PDA based analysis of steroidal compounds
The quantitative and quantitative analysis of five steroids [namely 20-hydroxyecdysone (1), pennogenin-3-Oβ-chacotrioside (2), dioscin (3), trillin (4), diosgenin ( 5)) was performed on Waters UPLC-QTOF Micromass system.The separation of analytes was carried out on ACE Ultra Core 2.5 Super C18 column (2.1 mm × 100 mm and particle size of 2.5 µm) and the column temperature was kept at 30ºC.The mobile phase consisted of water (0.1% formic acid) as solvent A and acetonitrile (0.1% formic acid) as solvent B, with a steep gradient programmed as: 0.0-0.3min, 18% B; 0.3-5 min, 18-60% B; 5.0-8.0 min, 60-85% B; 8.0-11.0min, 85-90% B;  The flow rate and injection volume were kept at 0.27 mL/min and 2 µL, respectively.Wavelength 195 nm was selected for the analysis and the results were expressed as mg of compound/g of dried extract ± SD.Further, method was validated for linearity, sensitivity, precision, recovery, stability, and reproducibility.Eight different concentrations (3.906-500 µg/mL) of stock solutions (0.5 mg/mL) of each compound were used to plot calibration curve.The calibration curve was plotted based on areas vs concentration of standards.The intra-day and inter-day precision were used to define repeatability and reproducibility of the method.The intra-day variation was assessed by performing three repetitive injections of the standard solution on the same day, while the interday variation was evaluated over three consecutive days.Further, the accuracy of the method was assessed using a recovery test which was calculated by adding the known concentrations of four different concentrations level to the sample and percentage quantitative recovery with the spiked amount was calculated.Further, concurrent qualitative and quantitative analysis of compounds 1-5 were performed in different organs of T. govanianum.

Macro and microelements analysis
Estimation of macro and micro-elements (Na, Ca, Mn, Cu, Zn, Fe, Mg, and K), along with heavy metals concentrations (Pb, Cd as toxic and Ni, Cr as essential) were determined in the different parts of the plant by using Shimadzu model AA 6300 Atomic Absorption Spectrophotometer (Tokyo Japan).Briefly, each plant part (0.50 g) of rhizomes, roots, rhizomatous buds, stems, leaves, and fruits was placed in a 100 mL volumetric flask, and 14 mL of acids mixture (HNO 3 : H 2 SO 4 : HClO 4 with ratio of 9:3:1) was added.The estimation of element was performed as described in the AOAC method 96,97 and results were expressed as mg/g of dried plant material ± SD.

Untargeted metabolomics of T. govanianum UHPLC-QTOF-MS/MS-based identification of metabolites
The metabolites were analysed using 6560 Ion Mobility Q-TOF LC/MS (Agilent, Santa Clara, USA).The separation of analytes was carried out on ACE Ultra Core 2.5 Super C18 column (2.1 mm × 100 mm and particle size of 2.5 µm).The gradient elution method consisted of mobile phases water (0.1% formic acid) as phase A and acetonitrile (0.1% formic acid) as phase B, with a steep gradient programmed as: 0.0-0.In metabolites profiling, the data was obtained in positive ion mode and processed through Mass Hunter software.Initially, the metabolites were identified using UV spectra, retention time, and MS/MS fragmentation.Further, for comprehensive chemical profiling, the data was processed through Mass Hunter (qualitative analysis software) and analysis of molecular features and confirmation of compounds in each sample was performed via the Molecular Feature Extractor (MFE) algorithm.Compounds were identified after fixing each parameter such as: retention time, intensity, mass fragmentation, and searched against the METLIN database to identify unknown metabolites in T. govanianum extracts.Further, most prominent metabolites were identified by analysing mass fragmentation, MS/MS patterns, molecular weight, UV absorption, and previous literature reports as well as all compounds were confirmed via the Human Metabolome Database (HMDB) (http:// www.hmdb.ca/), METLIN (http:// metlin.scrip ps.edu/), ChemSpider (http:// www.chems pider.com/) and Kyto Encyclopedia of Genes and Genomes (KEGG) (http:// www.kegg.com/).Identified compounds were looked for the possible structure through high-resolution MS and MS/MS spectrum analysis, and compared with online database.

In-vitro anti-Alzheimer's activity
The enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activity were performed based on Ellman's assay 98 .Enzymes hydrolyses the substrates (acetylthiocholine or butyryl thiocholine iodide) and convert them into thiocholine, which reacts with Ellman's reagent (DTNB) to produce "2-nitrobenzoic-5-mercaptothiocholine" and "5-thio-2-nitrobenzoate" which can be detected at 405 nm of wavelength 99 .Briefly, 160 μL of phosphate buffer (pH 7.0), 20 μL of enzyme (AChE/BChE; 0.22 U/mL), and 20 μL test solution (plant extracts, standard) were incubated for 10 min at 4 °C.Then the reaction was initiated by addition of 10 μL of substrate (acetylthiocholine iodide/butyrylthiocholine iodide 0.68 mM) and 10 μL DTNB (0.03 mmol/L).Thereafter, the reaction mixture was incubated for 30 min at 37 °C and absorbance was recorded at 405 nm in a where C is the activity of the enzyme without the test sample and T is the activity of the enzyme with the test sample.The results were expressed as IC 50 ± SD values.

Data analysis and visualization
Data were represented as mean ± standard deviation (SD) of three independent experiments.The data is centered, normalized (confidence level > 95%), and subjected for statistical analysis via Multi Experiment Viewer (MeV; v. 4.9.0) and Past 4.02 (v.1.0.0.0).Further, online statistical analysis such as eVenn, SRplote were also performed.The datasets of non-targeted metabolites were subjected to the SR plot software to generate the heat maps while targeted metabolites were subjected to the Past 4.02 software.For the activity part statistical analysis was carried out using analysis of variance (ANOVA) followed by Dunnett's multiple comparisons test.It was performed using GraphPad Prism software (v.8.0; GraphPad Software Inc., San.Diego, CA, USA).Values with p ≤ 0.05 were taken as statistically significant.

Conclusion
In this study, detailed metabolites compositional variation in different parts (roots, rhizomes, rhizomatous buds, stems, leaves, and fruits) of T. govanianum was explored for the first time that includes estimation of five steroidal compounds, sugar, and micro/macro elements via UPLC-PDA, UPLC-ELSD, and AAS, respectively.Comprehensively, more than 800 metabolites were identified through manual approach and METLIN data search in T. govanianum.Steroids was found most abundant class in the underground parts.Study also suggested that T. govanianum is a rich source of dioscin and can be converted easily to trillin and diosgenin.Further both can be converted into progesterone (a corticosteroid hormone).The presence of sex hormone precursor in T. govanianum strongly supports its traditional claims, as it is effective in sexual problems.In overall, the metabolomics insights the chemical information of T. govanianum that can act be a signature for the quality assessment of T. govanianum and its derived products.The study will also useful for agro-biotechnological interventions for sustainable cultivation.Furthermore, T. govanianum showed anti-alzheimer potential and can be targeted for the isolation of lead anti-alzheimer agents.The study will pave a way for the development phytopharmaceutical product.
fragment [M+H-Glu] + at m/z 181.09.This gave the information of peak 1 as sucrose which was identified in all the parts except stem sample of T. govanianum25 .Further, peaks 7 and 11 were identified as zizybeoside I [m/z 455.15 (M+Na) + ] and corchoionoside A [m/z 389.21 (M+H) + ], respectively, which were o-glycosyl compound (Table

Figure 4 .
Figure 4. (A) Doughnut diagram, Venn diagram, and social graph of metabolites identified using METLIN database in different organs of T. govanianum.(B) Venn network plot of identified compounds (METLIN database) in different organs of T. govanianum.

Figure 6 .
Figure 6.(A) Heat map-HCA, (B) VIP scores, and (C) HCA dendrogram analysis in the different organs of T. govanianum.*Heat map hierarchical clustering analysis, content of each metabolite was normalized to the complete linkage hierarchical clustering.Each example is visualized in a single column and each metabolite is represented by a single row.Brown indicates high abundance, whereas metabolites with low relative abundance are shown in blue.(B) Identified mass-to-charge ratio (m/z) with the variable importance in projection (VIP) scores that discriminate between specific organs.(C) Dendrogram of the investigated organs specific samples based on the metabolites obtained after MS data analysis.

Table 1 .
Quantification of steroidal compounds, free sugars, micro and macro elements in different organs of T. govanianum.*Data shown as mean ± SD, RB = Rhizomatous buds, *NQ = Not Quantified, **ND = Not Detected.